Research Projects Directory

Research Projects Directory

At this time, all listed projects are using data in the registered tier. The registered tier contains individual-level data from electronic health records, survey answers, and physical measurements. These data have been altered to protect participant privacy.

Note: Researcher Workbench users provide information about their research projects independently. Any views expressed in the Research Projects Directory belong to the relevant users and do not necessarily represent those of the All of Us Research Program.

Information in the Research Projects Directory is also cross-posted on AllofUs.nih.gov in compliance with the 21st Century Cures Act.

There are currently 214 active workspaces. This information was updated on 9/23/2020.

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Pdc obesity map 11102019

Project Purpose(s)

  • Population Health ...

Scientific Questions Being Studied

Exploring the data to determine obesity patterns by region in USA and by race/ethnicity

Scientific Approaches

Not available.

Anticipated Findings

I expect that the regional obesity maps generated with all of us data will parallel the cdc maps

Demographic Categories of Interest

Not available.

Research Team

Owner:

  • Paulette Chandler - Early Career Tenure-track Researcher, Massachusetts General Hospital

Collaborators:

  • Guohai Zhou - Early Career Tenure-track Researcher, Massachusetts General Hospital

PheWAS of mCNV/VNTR/STRs across populations

Project Purpose(s)

  • Ancestry ...

Scientific Questions Being Studied

The aim of our research is to link both common and rare tandem repeat (TR) expansions across the human genome to disease phenotypes across a varied and diverse patient population. Furthermore, we wish to model the modulation of these repeat expansions to explain how variations in repeat size and copy number translate to variable disease states, and develop genotype groupings based on these repeat expansion categories.

Scientific Approaches

We plan to use the vast phenotypic disease data available with the whole genome sequencing data to perform phenotype wide association studies (PheWAS) using a number of bioinformatic tools including BOLT-LMM and REGENIE. We then plan to analyze these results with R to identify statistically significant associations between rare tandem repeat variants and disease phenotypes. Additionally, we will attempt to identify if common tandem repeat copy number variations are associated with phenotypic expression.

Anticipated Findings

Our hope is that this study will identify several novel short tandem repeat (STR) and variable number tandem repeat (VNTR) variant candidates that may be explanatory for a number of human diseases, and potentially reveal targetable genomic regions/sequences for these diseases' treatment. Additionally, we hope to demonstrate that this kind of genetic survey of common and rare tandem repeats, which are generally ignored variant types, provides key scientific and clinical insight into human genetics and disease.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Adrian Bubie - Project Personnel, Icahn School of Medicine at Mount Sinai

potassium_level

Project Purpose(s)

  • Disease Focused Research (PMDD, PMS, ADHD, Periodical paralysis) ...

Scientific Questions Being Studied

We find that there might be some correlations between potassium level and four common diseases: PMS, PMDD, ADHD, Periodical paralysis. We think our findings can help us better understanding the diseases and find some effective treatments.

Scientific Approaches

We will use the datasets available on All of Us to find some patterns in a population level. We will make examine the potassium level and make some correlations between four common diseases.

Anticipated Findings

We think potassium level can affect the severity of the symptoms that different people might experience. Our findings can help us better understanding the four common diseases.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Chang Liu - Undergraduate Student, University of California, San Diego

Practice Analyses

Project Purpose(s)

  • Educational ...

Scientific Questions Being Studied

Interested in the intersection of human genetics and statistics - specifically interested in Alzheimer's, hormone responses and lipodema

Scientific Approaches

Interested in looking at the incidence of Alzheimer's, hormone responses, lipodema within the framework of their genetic basis.

Anticipated Findings

Hoping to connect genetic conditions with a particular causative factor and support better medical practices for all communities affected

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

  • Romeo B Celaya - Research Fellow, University of Arizona

Practice Analyses

Project Purpose(s)

  • Educational ...

Scientific Questions Being Studied

Interested in the intersection of human genetics and statistics - specifically interested in Alzheimer's, hormone responses and lipodema

Scientific Approaches

Interested in looking at the incidence of Alzheimer's, hormone responses, lipodema within the framework of their genetic basis.

Anticipated Findings

Hoping to connect genetic conditions with a particular causative factor and support better medical practices for all communities affected

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

  • Romeo B Celaya - Research Fellow, University of Arizona

Practice20200722

Project Purpose(s)

  • Educational ...

Scientific Questions Being Studied

Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.

Scientific Approaches

Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.

Anticipated Findings

None. Navigate and understand interface. Just learning how to use workbench.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Michelle Newell - Graduate Trainee, University of Arizona

Practice20200722

Project Purpose(s)

  • Educational ...

Scientific Questions Being Studied

Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.

Scientific Approaches

Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.Navigate and understand interface. Just learning how to use workbench.

Anticipated Findings

None. Navigate and understand interface. Just learning how to use workbench.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Michelle Newell - Graduate Trainee, University of Arizona

PracticeKM

Project Purpose(s)

  • Educational ...

Scientific Questions Being Studied

This workspace will be used to prepare instructor content and analysis protocols for a course-based research laboratory class supported by the Towson University Research Enhancement Program. The purpose of this course is for students to have the experience of developing a research question in human health and then they will design and implement an analysis of publicly available data to answer their research question. The student research projects will focus on medical health and public health topics. As well as learning skills important in medical and epidemiological research, students will be able ask questions that could lead to better understanding of and treatment for diseases in traditionally under-served populations.

Scientific Approaches

Data analysis will be run in an NIH-approved "Researcher Workbench" platform using Jupyter Notebook and R. The questions students will ask will be dependent on what data All of Us has available to researchers at the time of the course. These data will include health data, physical measurement data, biospecimen-related data, and genomic data.

Anticipated Findings

As well as learning skills important in medical and epidemiological research, students will be able ask questions that could lead to better understanding of and treatment for diseases in traditionally under-served populations. We also hope this course will encourage undergraduate students to consider careers in medical research.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

  • Kathryn McDougal - Other, Towson University

Predictors of Endometriosis

Project Purpose(s)

  • Disease Focused Research (endometriosis) ...

Scientific Questions Being Studied

We aim to quantify predictors of endometriosis and investigate the association between race/ethnicity, urban/rural hospital status, hospital bed size, marital status, census region, infertility, and PCOS diagnosis with the diagnosis of endometriosis.

Historically, Black and Hispanic women have lower rates of diagnosed endometriosis. We hypothesize that when barriers to accessing care are accounted for, the rate of endometriosis will be the same across racial/ethnic groups of women and this disparity in the diagnosis of endometriosis will be attenuated. We predict that rural hospital status will have a lower diagnostic rate of endometriosis when compared to urban hospital status.

Scientific Approaches

We hope to assemble a cohort of women who have had a well-woman exam in the past 3 years. Of these women, we would like to see how many of these women have a diagnosis of endometriosis and compare them to women with no diagnosis. We would like to compare these two cohorts on demographic data to assess whether rates of diagnosis differ between groups. Assembling these two cohorts of women will allow us to gather more accurate information about the true prevalence rate of endometriosis, which has thus far been difficult to quantify.

Anticipated Findings

with this dataset, there will be no disparity between racial/ethnic groups. We believe the current disparity reflected in the literature represents issues in accessing quality care. Our findings can help guide clinical practice and help address health disparities between those who are able to receive a diagnosis for endometriosis and those who are not.

Demographic Categories of Interest

  • Race / Ethnicity
  • Geography
  • Access to Care
  • Income Level

Research Team

Owner:

  • Sana Khan - Graduate Trainee, University of Arizona

Predictors of Endometriosis

Project Purpose(s)

  • Disease Focused Research (endometriosis) ...

Scientific Questions Being Studied

We aim to quantify predictors of endometriosis and investigate the association between race/ethnicity, urban/rural hospital status, hospital bed size, marital status, census region, infertility, and PCOS diagnosis with the diagnosis of endometriosis.

Historically, Black and Hispanic women have lower rates of diagnosed endometriosis. We hypothesize that when barriers to accessing care are accounted for, the rate of endometriosis will be the same across racial/ethnic groups of women and this disparity in the diagnosis of endometriosis will be attenuated. We predict that rural hospital status will have a lower diagnostic rate of endometriosis when compared to urban hospital status.

Scientific Approaches

We hope to assemble a cohort of women who have had a well-woman exam in the past 3 years. Of these women, we would like to see how many of these women have a diagnosis of endometriosis and compare them to women with no diagnosis. We would like to compare these two cohorts on demographic data to assess whether rates of diagnosis differ between groups. Assembling these two cohorts of women will allow us to gather more accurate information about the true prevalence rate of endometriosis, which has thus far been difficult to quantify.

Anticipated Findings

with this dataset, there will be no disparity between racial/ethnic groups. We believe the current disparity reflected in the literature represents issues in accessing quality care. Our findings can help guide clinical practice and help address health disparities between those who are able to receive a diagnosis for endometriosis and those who are not.

Demographic Categories of Interest

  • Race / Ethnicity
  • Geography
  • Access to Care
  • Income Level

Research Team

Owner:

  • Sana Khan - Graduate Trainee, University of Arizona

Predictors of Endometriosis

Project Purpose(s)

  • Disease Focused Research (endometriosis) ...

Scientific Questions Being Studied

We aim to quantify predictors of endometriosis and investigate the association between race/ethnicity, urban/rural hospital status, hospital bed size, marital status, census region, infertility, and PCOS diagnosis with the diagnosis of endometriosis.

Historically, Black and Hispanic women have lower rates of diagnosed endometriosis. We hypothesize that when barriers to accessing care are accounted for, the rate of endometriosis will be the same across racial/ethnic groups of women and this disparity in the diagnosis of endometriosis will be attenuated. We predict that rural hospital status will have a lower diagnostic rate of endometriosis when compared to urban hospital status.

Scientific Approaches

We hope to assemble a cohort of women who have had a well-woman exam in the past 3 years. Of these women, we would like to see how many of these women have a diagnosis of endometriosis and compare them to women with no diagnosis. We would like to compare these two cohorts on demographic data to assess whether rates of diagnosis differ between groups. Assembling these two cohorts of women will allow us to gather more accurate information about the true prevalence rate of endometriosis, which has thus far been difficult to quantify.

Anticipated Findings

with this dataset, there will be no disparity between racial/ethnic groups. We believe the current disparity reflected in the literature represents issues in accessing quality care. Our findings can help guide clinical practice and help address health disparities between those who are able to receive a diagnosis for endometriosis and those who are not.

Demographic Categories of Interest

  • Race / Ethnicity
  • Geography
  • Access to Care
  • Income Level

Research Team

Owner:

  • Sana Khan - Graduate Trainee, University of Arizona

Pregnancy After ACL Injury

Project Purpose(s)

  • Disease Focused Research (anterior cruciate ligament injury, osteoarthritis)
  • Population Health ...

Scientific Questions Being Studied

Do pregnancy-related outcomes differ among women with and without a history of a knee injury (specifically an anterior cruciate ligament [ACL] injury) and if so does the presence of knee osteoarthritis or other related diseases/disorders (e.g., high blood pressure, obesity) mediate this relationship?
This is exploratory at this point to help formalize a research question. Evidence suggests that people with a history of an ACL injury are less physically active and report lower quality of life than peers without a history of an ACL injury. There is limited data about whether pregnancy outcomes may differ based on injury history.

Scientific Approaches

The All of Us dataset will be used to identify females with and without a history of an ACL injury. The two groups will be matched on age and other possible factors that may influence injury risk and pregnancy outcomes.

Anticipated Findings

This exploratory analysis will help inform future studies to better understand if pregnancy-outcomes differ between females with or without a history of ACL injury. If so, this project will provide preliminary evidence about which factors may help explain why there is a difference.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Jeffrey Driban - Mid-career Tenured Researcher, Tufts University

Prehypertension Epidemiology

Project Purpose(s)

  • Other Purpose (This work is a result of an All of Us Research Program Demonstration Project. The projects are efforts by the Program designed to meet the program's goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. This work was reviewed and overseen by the All of Us Research Program Science Committee and the Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use) ...

Scientific Questions Being Studied

In this demonstration project, we propose to replicate the association between race, prehypertension, and associated risk factors, using the All of Us (AoU) participant provided information as well as clinical data. Specific questions of interest include:
1. What is the prevalence of prehypertension in the AoU data?
2. How to define prehypertensive, normotensive, and hypertensive cohorts in the AoU data?
3. What is the association between race and prehypertension?

Scientific Approaches

We will use internationally-defined blood pressure ranges to characterize prehypertensive, normotensive, and hypertensive groups. We will generate summary statistics for various hypertension groupsRace will be categorized according to the definitions of the US Census Bureau. We will stratify results by race to assess the interaction between race and prehypertension. Jupyter Notebook and R will be used used to perform the analyses.

Anticipated Findings

We anticipate the prevalence of prehypertension to be associated with age, race and ethnicity, heart disease, and diabetes as reported in previous literature.

Demographic Categories of Interest

  • Race / Ethnicity

Research Team

Owner:

  • Vignesh Subbian - Early Career Tenure-track Researcher, University of Arizona

Collaborators:

  • John Ehiri
  • Baran Balkan - Project Personnel, University of Arizona

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Project Purpose(s)

  • Disease Focused Research (qqq) ...

Scientific Questions Being Studied

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Scientific Approaches

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Anticipated Findings

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Demographic Categories of Interest

  • Race / Ethnicity

Research Team

Owner:

  • Aaron Abend - Senior Researcher, Autoimmune Registry, Inc.

RacialEthnicDifferences_AnthropoLipidALT

Project Purpose(s)

  • Disease Focused Research (Obesity)
  • Other Purpose (This work is the result of an All of Us Research Program Demonstration Project. Demonstration Projects are efforts by the All of Us Research Program designed to meet the goal of ensuring the quality and utility of the Research Hub as a resource for accelerating precision medicine. This work has been approved, reviewed, and overseen by the All of Us Research Program Science Committee and Data and Research Center to ensure compliance with program policy.) ...

Scientific Questions Being Studied

Obesity is one of the most important risks for many diseases in the United States and across the world. Differences in body weight and shape across gender and race/ethnicity have been extensively described. We sought to replicate these differences and evaluate newly emerging data from the All of Us Research Program (AoU). In this project, we ask the scientific question: How do individuals from different genders and different racial/ethnic groups in the All Of Us dataset differ with respect to weight, waist and hip circumferences, cholesterol levels and levels of alanine aminotransferase?

Scientific Approaches

Within each ethnic/racial group and each gender group, we first visually examine histograms of each outcome variable to determine the presence of any major outliers that may represent measurement errors. Then we tabulated the mean values and other descriptive statistics for continuous variables such as waist and hip circumferences. We also determined the proportion of individuals with abdominal obesity. To formally test for differences among groups and to adjust for age and other covariates, we will use linear regression, transforming variables to conform to assumptions of linear regression. Data for race and ethnicity was obtained from participants in participant-provided information (PPI). Biological sex at birth, height, weight, waist circumference (WC), and hip circumference measurements were obtained according to AoU baseline visit protocols. Levels of alanine aminotransferase (ALT) were obtained from the EHR records of participants.

Anticipated Findings

For this study, we anticipate that we will be able to replicate known differences in body weight and shape across gender and race/ethnicity. We anticipate that we will find racial/ethnic and gender disparities related to ALT, a surrogate marker of hepatic steatosis. We anticipate the ability to evaluate the consistency of the All of Us cohort with national averages related to obesity and indicate that this resource is likely to be a major source of scientific inquiry and discovery. This project will serve to demonstrate the quality, utility, and diversity of the All of Us data and tools and the power of gathering multiple data sources for a single set of phenotypes, providing researchers options for study design and validation.

Demographic Categories of Interest

  • Race / Ethnicity
  • Sex at Birth

Research Team

Owner:

  • Yann Klimentidis - Mid-career Tenured Researcher, University of Arizona

Collaborators:

  • Roxana Loperena Cortes - Other, All of Us Program Operational Use
  • Jason Karnes - Early Career Tenure-track Researcher, University of Arizona
  • Andrea Ramirez - Other, All of Us Program Operational Use
  • Amit Arora - Graduate Trainee, University of Arizona
  • Lina Sulieman - Other, All of Us Program Operational Use

REAL ARI Workspace

Project Purpose(s)

  • Disease Focused Research (Autoimmune diseases) ...

Scientific Questions Being Studied

The goal of our research is to determine prevalence of autoimmune diseases, individually and as a class of disease, in the US. This work will help understand the likelihood of having autoimmune disease and we hope it will improve the ability of doctors to diagnose patients as it will establish the prior probability of having one of these many diseases.

Scientific Approaches

We will create three data sets for analysis:

1. A list of diseases rated in the following ways:

a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism

b. Autoinflammatory versus autoimmune flag

c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause

2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics

Anticipated Findings

The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.

Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Aaron Abend - Senior Researcher, Autoimmune Registry, Inc.

Collaborators:

  • Priya Padathula - Project Personnel, Autoimmune Registry, Inc.
  • Jeffrey Green - Project Personnel, Autoimmune Registry, Inc.
  • Darrison Haftarczyk - Research Assistant, Autoimmune Registry, Inc.

Researcher Workbench learning

Project Purpose(s)

  • Other Purpose (Learning Researcher Workbench and exploring AllOfUs data.) ...

Scientific Questions Being Studied

This workspace will be used for learning Research Workbench and exploring the data available in the AllOfUs tools.
I am planning to explore how does the prevalence of some medical conditions in AllOfUs compare to the national data that is reported in various medical publications.
Planning to explore also the availability of data for Pediatric ages in All Of Us. It will also help me understand if the data can be used for neonatal research.

Scientific Approaches

Planning on exploring the EHR data and the surveys data for learning the platform and exploring the data.

Anticipated Findings

I anticipate finding that the prevalence of various medical conditions is within the published ranges of prevalence in US.
In terms of ages for which AllOfUs data is available, I expect to find that the younger the pediatric patient, the least number of subjects will be available in AllOfUs.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Corneliu Antonescu - Mid-career Tenured Researcher, University of Arizona

Researcher Workbench learning

Project Purpose(s)

  • Other Purpose (Learning Researcher Workbench and exploring AllOfUs data.) ...

Scientific Questions Being Studied

This workspace will be used for learning Research Workbench and exploring the data available in the AllOfUs tools.
I am planning to explore how does the prevalence of some medical conditions in AllOfUs compare to the national data that is reported in various medical publications.
Planning to explore also the availability of data for Pediatric ages in All Of Us. It will also help me understand if the data can be used for neonatal research.

Scientific Approaches

Planning on exploring the EHR data and the surveys data for learning the platform and exploring the data.

Anticipated Findings

I anticipate finding that the prevalence of various medical conditions is within the published ranges of prevalence in US.
In terms of ages for which AllOfUs data is available, I expect to find that the younger the pediatric patient, the least number of subjects will be available in AllOfUs.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Corneliu Antonescu - Mid-career Tenured Researcher, University of Arizona

Revision_after_HTN_code_review

Project Purpose(s)

  • Other Purpose (This work is an AoU demo project. Demo projects are efforts by the AoU Research Program designed to meet the program goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. As an approved demo project, this work was reviewed and overseen by the AoU Research Program Science Committee and the AoU Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use. ) ...

Scientific Questions Being Studied

We are using the All of Us Researcher Workbench interface to answer the question, "Is hypertension prevalence in the All of Us Research Program similar to hypertension prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES) ?". Clinical approaches to understanding and treating hypertension may benefit from the integration of a precision medicine approach that integrates data on environments, social determinants of health, behaviors, and genomic factors that contribute to hypertension risk. Hypertension is a major public health concern and remains a leading risk factor for stroke and cardiovascular disease.

Scientific Approaches

In this cross-sectional, population-based study, we used All of Us baseline data from patient (age>18) provided information (PPI) surveys and electronic health record (EHR) blood pressure measurements and retrospectively examined the prevalence of hypertension in the EHR cohort using Systemized Nomenclature of Medicine (SNOMED codes and blood pressure medications recorded in the EHR. We used the EHR data (SNOMED codes on 2 distinct dates and at least one hypertension medication) as the primary definition, and then add subjects with elevated systolic or elevated diastolic blood pressure on measurements 2 and 3 from PPI. We extracted each participant’s detailed dates of SNOMED code for essential hypertension from the Researcher Workbench table ‘cb_search_all_events’. We calculated an age-standardized HTN prevalence according to the age distribution of the U.S. Census, using 3 groups (18-39, 40-59, ≥ 60).

Anticipated Findings

The prevalence of hypertension in the All of Us cohort is similar to that of published literature. All of Us age-adjusted HTN prevalence was 27.9% compared to 29.6% in National Health and Nutrition Examination Survey. The All of Us cohort is a growing source of diverse longitudinal data that can be utilized to study hypertension nationwide. The prevalence of hypertension varies in the United States (U.S.) by age, sex, and socioeconomic status. Hypertension can often be treated successfully with medication, and prevented or delayed with lifestyle modifications. Even with these established hypertension intervention and prevention strategies, the prevalence of hypertension continues to be at levels of public health concern. The diversity within All of Us may provide insight into factors relevant to hypertension prevention and treatments in a variety of social and geographic contexts and population strata in the U.S.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Guohai Zhou - Early Career Tenure-track Researcher, Massachusetts General Hospital